SG: Exploring the Impact of Model (Mis) Specification on Empirical Divergence-Time Estimates

系统发生树-物种之间进化关系的估计-已经成为系统学，进化生物学，生态学，分子生物学和流行病学的几乎所有研究领域的核心，因为它们提供了基本和明确的历史观点。系统发育学已经将其影响力从科学领域扩展到公共领域，为病原体的监视和监测、疫苗设计和保护优先事项的决策提供信息。虽然许多谱系是基于从现存物种（或菌株）收集的分子序列数据（DNA），但这些树也可以提供有关谱系内绝对或相对分支时间的信息。 这种时间信息对许多问题都至关重要，例如推断病毒的强毒株何时首次出现以及估计它的变化速度。 这些考虑促使发展了大量的数学模型来推断进化树的时间尺度。该项目旨在使用经验数据集评估这些数学模型的可靠性，并将向研究人员和公众提供使用这些方法的最佳实践。通过加州大学历史上的黑人学院和大学倡议和美国戴维斯倡议最大限度地提高学生多样性招募的本科生将接受统计系统发育方法和生物信息学的培训。 所有开发的软件都将在开源许可证下免费分发。 研究人员还将开发一个新的，独立的研讨会和相关的教学材料贝叶斯分歧时间估计方法被广泛使用，包括研究人员谁不直接在系统发育research.The本研究的主要目标是探索贝叶斯方法估计物种分歧时间的统计行为在一个经验设置。这一主要目标将通过将所有当前实现的松弛时钟模型和校准方法应用于大样本的经验数据集来实现：（1）揭示发散时间估计对指定的松弛时钟模型/校准方法的敏感程度;（2）探索三个主要模型组件-分支率先验，节点年龄先验，和校准方法--关于发散时间估计;（3）使用稳健的贝叶斯模型比较方法评估候选弛豫时钟模型库与真实的数据的相对拟合;（4）开发分析协议并实施管道，以自动有效探索弛豫时钟模型空间，用于实证分析。促进更仔细的模型选择将提高我们估计分歧时间的能力，这反过来又将使科学界和更广泛的社区受益。

Phylogenetic trees - estimates of the evolutionary relationships among species - have become central to virtually all areas of research in systematics, evolutionary biology, ecology, molecular biology, and epidemiology because of the essential and explicit historical perspectives they provide. Phylogenies have extended the branches of their influence from the scientific to the public realm, informing decisions regarding the surveillance and monitoring of pathogens, vaccine design, and conservation priorities. Although many phylogenies are based on molecular sequence data (DNA) collected from extant species (or strains), these trees can also provide information regarding the absolute or relative branching times within a lineage. This temporal information is critical to many questions, such as inferring when a virulent strain of a virus first arose and estimating how quickly it is changing. These considerations have motivated the development of a large number of mathematical models for inferring the time scale of evolutionary trees. This project seeks to assess the reliability of these mathematical models using empirical datasets, and will inform researchers and public alike on the best practices for using these methods. Undergraduates recruited through the University of California Historically Black Colleges and Universities initiative and the US Davis Initiative for Maximizing Student Diversity will be trained in statistical phylogenetic methods and bioinformatics. All software developed will be distributed freely under open-source licenses. The researcher will also develop a new, stand-alone workshop and associated teaching materials on Bayesian divergence-time estimation methods to be used broadly, including by researchers who do not work directly in phylogenetic research.The primary objective of this research is to explore the statistical behavior of Bayesian methods for estimating species divergence times in an empirical setting. This main goal will be achieved by applying all currently implemented relaxed-clock models and calibration methods to a large sample of empirical datasets to: (1) reveal the extent to which divergence-time estimates are sensitive to the specified relaxed-clock model/calibration method; (2) explore the relative influence of the three primary model components - branch-rate priors, node-age priors, and calibration approaches - on divergence-time estimates; (3) assess the relative fit of the pool of candidate relaxed-clock models to real data using robust Bayesian model-comparison methods; and (4) develop analytical protocols and implement pipelines that automate the efficient exploration of relaxed-clock model space for empirical analyses. Facilitating more careful model selection will improve our ability to estimate divergence times, which, in turn, will broadly benefit scientific and broader communities.